Consider a scenario where a person would like to identify a piece of music that has a distinctive theme. The person remembers this musical theme very well; however, may not know the title, or composer, or its country of origin, or its key signature, or any similar identifying characteristic. Further, the person cannot write down the music because he or she does not know musical notation.
One possible recourse for this person would be to consult a book of musical themes. Originally, these books required the ability to read/write music in order to find a piece of music and so would not be helpful to a non-musician. However, some books characterize musical themes using the Parsons code, also known as melody contour or rough contour. Generally, this code is a representation of the melody of a musical theme that only requires the reader to know whether the pitch of each consecutive note in the theme is higher, lower or the same as the last note. The drawback to this is that even very different musical themes can exhibit identical or similar contours, and so a search by contour alone often produces multiple “false positives” or requires unreasonably long queries.
Another option available to the aforementioned person wanting to identify a piece of music is to employ a computer-based musical information retrieval system. In general, these systems involve a user making a query that represents the musical theme being sought via some type of user interface. The input is typically characterized in some manner and then compared to a database of similarly characterized musical themes in an attempt to find a match. The system then reports the matching theme(s) to the user. For example, the matching theme title(s) could be displayed to the user on a computer monitor screen.
The user interfaces employed in these conventional musical information retrieval systems vary greatly. Most employ some form of a graphical user interface that a user employs to enter information about the theme. For example, a user might be required to enter notes onto a representation of a musical staff. Thus, the user would need to know how to write music. Another example might involve a user entering a Parsons code representation of the musical theme being sought. Yet another example might involve the user humming the theme which is captured via a microphone.
In regard to the content databases employed in musical information retrieval systems, most store music as musical score-based (or note-based) information in one of several widely known encoding formats, such as MIDI, MusicXML, MuseData and Humdrum. Unfortunately, these encoding formats do not lend themselves to efficient theme searching. As a result, some systems employ more search-friendly characterizations of the stored musical themes. For example, pitch characterizations including the Parsons code are often used. Thus, queries by a user are first characterized in the same manner as the stored musical themes before being compared.